Liu, Song

32 publications

AAAI 2025 DMT-RoleBench: A Dynamic Multi-Turn Dialogue Based Benchmark for Role-Playing Evaluation of Large Language Model and Agent Dingbo Yuan, Yipeng Chen, Guodong Liu, Chenchen Li, Chengfu Tang, Dongxu Zhang, Zhenkui Wang, Xudong Wang, Song Liu
NeurIPS 2025 Direct Fisher Score Estimation for Likelihood Maximization Sherman Khoo, Yakun Wang, Song Liu, Mark Beaumont
NeurIPS 2025 ForceFM: Enhancing Protein-Ligand Predictions Through Force-Guided Flow Matching Huanlei Guo, Song Liu, Bingyi Jing
UAI 2025 Guiding Time-Varying Generative Models with Natural Gradients on Exponential Family Manifold Song Liu, Leyang Wang, Yakun Wang
ICLRW 2025 Guiding Time-Varying Generative Models with Natural Gradients on Exponential Family Manifold Song Liu, Leyang Wang, Yakun Wang
AISTATS 2025 High-Dimensional Differential Parameter Inference in Exponential Family Using Time Score Matching Daniel James Williams, Leyang Wang, Qizhen Ying, Song Liu, Mladen Kolar
NeurIPS 2025 Missing Data Imputation by Reducing Mutual Information with Rectified Flows Jiahao Yu, Qizhen Ying, Leyang Wang, Ziyue Jiang, Song Liu
ICML 2025 Score Matching with Missing Data Josh Givens, Song Liu, Henry Reeve
ECML-PKDD 2024 A Merge Sort Based Ranking System for the Evaluation of Large Language Models Chenchen Li, Linfeng Shi, Chunyi Zhou, Zhaoxin Huan, Chengfu Tang, Xiaolu Zhang, Xudong Wang, Jun Zhou, Song Liu
NeurIPS 2024 Conditional Outcome Equivalence: A Quantile Alternative to CATE Josh Givens, Henry W J Reeve, Song Liu, Katarzyna Reluga
NeurIPSW 2024 Lightspeed Black-Box Bayesian Optimization via Local Score Matching Yakun Wang, Sherman Khoo, Song Liu
ICML 2024 Minimizing $f$-Divergences by Interpolating Velocity Fields Song Liu, Jiahao Yu, Jack Simons, Mingxuan Yi, Mark Beaumont
ICML 2024 Sequential Neural Score Estimation: Likelihood-Free Inference with Conditional Score Based Diffusion Models Louis Sharrock, Jack Simons, Song Liu, Mark Beaumont
ICML 2023 Approximate Stein Classes for Truncated Density Estimation Daniel James Williams, Song Liu
AISTATS 2023 Density Ratio Estimation and Neyman Pearson Classification with Missing Data Josh Givens, Song Liu, Henry W. J. Reeve
NeurIPSW 2023 DiffDock-Site: A Novel Paradigm for Enhanced Protein-Ligand Predictions Through Binding Site Identification Huanlei Guo, Song Liu, Mingdi Hu, Yilun Lou, Bingyi Jing
ICML 2023 MonoFlow: Rethinking Divergence GANs via the Perspective of Wasserstein Gradient Flows Mingxuan Yi, Zhanxing Zhu, Song Liu
JMLR 2022 Estimating Density Models with Truncation Boundaries Using Score Matching Song Liu, Takafumi Kanamori, Daniel J. Williams
NeurIPS 2022 Estimating the Arc Length of the Optimal ROC Curve and Lower Bounding the Maximal AUC Song Liu
CVPRW 2022 NTIRE 2022 Spectral Recovery Challenge and Data Set Boaz Arad, Radu Timofte, Rony Yahel, Nimrod Morag, Amir Bernat, Yuanhao Cai, Jing Lin, Zudi Lin, Haoqian Wang, Yulun Zhang, Hanspeter Pfister, Luc Van Gool, Shuai Liu, Yongqiang Li, Chaoyu Feng, Lei Lei, Jiaojiao Li, Songcheng Du, Chaoxiong Wu, Yihong Leng, Rui Song, Mingwei Zhang, Chongxing Song, Shuyi Zhao, Zhiqiang Lang, Wei Wei, Lei Zhang, Renwei Dian, Tianci Shan, Anjing Guo, Chengguo Feng, Jinyang Liu, Mirko Agarla, Simone Bianco, Marco Buzzelli, Luigi Celona, Raimondo Schettini, Jiang He, Yi Xiao, Jiajun Xiao, Qiangqiang Yuan, Jie Li, Liangpei Zhang, Taesung Kwon, Dohoon Ryu, Hyokyoung Bae, Hao-Hsiang Yang, Hua-En Chang, Zhi-Kai Huang, Wei-Ting Chen, Sy-Yen Kuo, Junyu Chen, Haiwei Li, Song Liu, Sabari Nathan, K. Uma, B. Sathya Bama, S. Mohamed Mansoor Roomi
ACML 2022 Sliced Wasserstein Variational Inference Mingxuan Yi, Song Liu
AAAI 2021 A General Class of Transfer Learning Regression Without Implementation Cost Shunya Minami, Song Liu, Stephen Wu, Kenji Fukumizu, Ryo Yoshida
NeurIPSW 2021 Continual Density Ratio Estimation Yu Chen, Song Liu, Tom Diethe, Peter Flach
ICCV 2021 HiT: Hierarchical Transformer with Momentum Contrast for Video-Text Retrieval Song Liu, Haoqi Fan, Shengsheng Qian, Yiru Chen, Wenkui Ding, Zhongyuan Wang
NeurIPS 2019 Fisher Efficient Inference of Intractable Models Song Liu, Takafumi Kanamori, Wittawat Jitkrittum, Yu Chen
ICML 2019 Heterogeneous Model Reuse via Optimizing Multiparty Multiclass Margin Xi-Zhu Wu, Song Liu, Zhi-Hua Zhou
NeurIPS 2017 Trimmed Density Ratio Estimation Song Liu, Akiko Takeda, Taiji Suzuki, Kenji Fukumizu
ICML 2016 Structure Learning of Partitioned Markov Networks Song Liu, Taiji Suzuki, Masashi Sugiyama, Kenji Fukumizu
AAAI 2015 Support Consistency of Direct Sparse-Change Learning in Markov Networks Song Liu, Taiji Suzuki, Masashi Sugiyama
AISTATS 2014 Bias Reduction and Metric Learning for Nearest-Neighbor Estimation of Kullback-Leibler Divergence Yung-Kyun Noh, Masashi Sugiyama, Song Liu, Marthinus Christoffel du Plessis, Frank Chongwoo Park, Daniel D. Lee
ECML-PKDD 2013 Direct Learning of Sparse Changes in Markov Networks by Density Ratio Estimation Song Liu, John A. Quinn, Michael U. Gutmann, Masashi Sugiyama
NeurIPS 2012 Density-Difference Estimation Masashi Sugiyama, Takafumi Kanamori, Taiji Suzuki, Marthinus D. Plessis, Song Liu, Ichiro Takeuchi